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What is the duration of the AWS Certified Machine Learning - Specialty

• Number of Questions: 54
• Language : English, Japanese, Korean, and Simplified Chinese
• Passing Score: 720
• Length of Examination: 130 minutes
• Format: Multiple choices, multiple answers

Reference: https://d1.awsstatic.com/training-and-certification/docs-ml/AWS%20Certified%20Machine%20Learning%20-%20Specialty_Exam%20Guide%20(1).pdf

Introduction to AWS Certified Machine Learning Specialty Exam

The AWS Certified Machine Learning Exam - Special Exam (MLS-C01) is designed for people who have a development or data science function. This exam validates a candidate's ability to create, train, adapt and implement machine learning (ML) models using the AWS cloud. Validation of a candidate's ability to design, implement, implement and maintain ML solutions for certain business problems. It will validate the candidate's ability to: Select and justify the appropriate LD approach for a given business problem. Identify the appropriate AWS services to implement ML solutions. Design and implement scalable, economic, reliable and safe ML solutions.

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Start Preparation with Study Guide

There are many books created to help candidates learn the exam topics. Still, only a few allow one to do this quickly and effectively. One of the most relevant study guides is “Machine Learning In The AWS Cloud” by Abhishek Mishra. You can easily buy it from Amazon and start your preparation as soon as possible. This is the perfect material for applicants to understand most common machine learning practices in the AWS cloud. It enhances one’s capabilities to perform well in the exam and in the workplace since it contains real-world practical examples and classification of business problems.

Candidates are expected to go through this book and clear their knowledge of the basics and specifics by mastering the two parts. The first one introduces the reader to the main concepts of machine learning and how they are utilized to solve the problems. The other part focuses on the cloud-based ML experience. It also introduces the use of Amazon Sagemaker and how it assists in overcoming complex issues professionals can face while performing day-to-day tasks.

Once you grasp all the information included in this book, you will also gain skills needed to solve computer vision problems with Amazon Rekognition. In addition, you will learn more about the core features of engineering, model building, and visualizing data. All this is explained in the easy-to-understand format due to sidebars, source code examples, and illustrations in each chapter. With such preparation, one boosts chances to ace the exam on the first attempt.

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